meka.experiment

Class MekaClassifierSplitEvaluator

java.lang.Object

weka.experiment.ClassifierSplitEvaluator

meka.experiment.MekaClassifierSplitEvaluator

All Implemented Interfaces:

java.io.Serializable, MekaSplitEvaluator, weka.core.AdditionalMeasureProducer, weka.core.OptionHandler, weka.core.RevisionHandler, weka.experiment.SplitEvaluator

public class MekaClassifierSplitEvaluator
extends weka.experiment.ClassifierSplitEvaluator
implements MekaSplitEvaluator

A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.

Valid options are:

 -W <class name>
  The full class name of the classifier.
  eg: weka.classifiers.bayes.NaiveBayes
 

 -C <index>
  The index of the class for which IR statistics
  are to be output. (default 1)
 

 -I <index>
  The index of an attribute to output in the
  results. This attribute should identify an
  instance in order to know which instances are
  in the test set of a cross validation. if 0
  no output (default 0).
 

 -P
  Add target and prediction columns to the result
  for each fold.
 

 -no-size
  Skips the determination of sizes (train/test/classifier)
  (default: sizes are determined)
 

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 

All options after -- will be passed to the classifier.

Version:

$Revision: 10376 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MekaClassifierSplitEvaluator() No args constructor.

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	classifierTipText() Returns the tip text for this property
java.lang.Object[]	getKey() Gets the key describing the current SplitEvaluator.
java.lang.String[]	getKeyNames() Gets the names of each of the key columns produced for a single run.
java.lang.Object[]	getKeyTypes() Gets the data types of each of the key columns produced for a single run.
java.lang.Object[]	getResult(weka.core.Instances train, weka.core.Instances test) Gets the results for the supplied train and test datasets.
java.lang.String[]	getResultNames() Gets the names of each of the result columns produced for a single run.
java.lang.Object[]	getResultTypes() Gets the data types of each of the result columns produced for a single run.
java.lang.String	getRevision() Returns the revision string.
int	getTotalNumClasses() Returns the overal number of classes.
java.lang.String	globalInfo() Returns a string describing this split evaluator
void	setClassifier(weka.classifiers.Classifier newClassifier) Sets the classifier.
void	setTotalNumClasses(int value) Sets the overal number of classes.

Methods inherited from class weka.experiment.ClassifierSplitEvaluator

enumerateMeasures, getAttributeID, getClassForIRStatistics, getClassifier, getMeasure, getNoSizeDetermination, getOptions, getPredTargetColumn, getRawResultOutput, listOptions, noSizeDeterminationTipText, setAdditionalMeasures, setAttributeID, setClassForIRStatistics, setClassifierName, setNoSizeDetermination, setOptions, setPredTargetColumn, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.experiment.SplitEvaluator

getRawResultOutput, setAdditionalMeasures

Constructor Detail

MekaClassifierSplitEvaluator

public MekaClassifierSplitEvaluator()

No args constructor.

Method Detail

setTotalNumClasses

public void setTotalNumClasses(int value)

Sets the overal number of classes.

Specified by:

setTotalNumClasses in interface MekaSplitEvaluator

Parameters:

value - the number of classes

getTotalNumClasses

public int getTotalNumClasses()

Returns the overal number of classes.

Specified by:

getTotalNumClasses in interface MekaSplitEvaluator

Returns:

the number of classes

globalInfo

public java.lang.String globalInfo()

Returns a string describing this split evaluator

Overrides:

globalInfo in class weka.experiment.ClassifierSplitEvaluator

Returns:

a description of the split evaluator suitable for displaying in the explorer/experimenter gui

getKeyTypes

public java.lang.Object[] getKeyTypes()

Gets the data types of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKeyTypes in interface weka.experiment.SplitEvaluator

Overrides:

getKeyTypes in class weka.experiment.ClassifierSplitEvaluator

Returns:

an array containing objects of the type of each key column. The objects should be Strings, or Doubles.

getKeyNames

public java.lang.String[] getKeyNames()

Gets the names of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKeyNames in interface weka.experiment.SplitEvaluator

Overrides:

getKeyNames in class weka.experiment.ClassifierSplitEvaluator

Returns:

an array containing the name of each key column

getKey

public java.lang.Object[] getKey()

Gets the key describing the current SplitEvaluator. For example This may contain the name of the classifier used for classifier predictive evaluation. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKey in interface weka.experiment.SplitEvaluator

Overrides:

getKey in class weka.experiment.ClassifierSplitEvaluator

Returns:

an array of objects containing the key.

getResultTypes

public java.lang.Object[] getResultTypes()

Gets the data types of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

Specified by:

getResultTypes in interface weka.experiment.SplitEvaluator

Overrides:

getResultTypes in class weka.experiment.ClassifierSplitEvaluator

Returns:

an array containing objects of the type of each result column. The objects should be Strings, or Doubles.

getResultNames

public java.lang.String[] getResultNames()

Gets the names of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

Specified by:

getResultNames in interface weka.experiment.SplitEvaluator

Overrides:

getResultNames in class weka.experiment.ClassifierSplitEvaluator

Returns:

an array containing the name of each result column

getResult

public java.lang.Object[] getResult(weka.core.Instances train,
                           weka.core.Instances test)
                             throws java.lang.Exception

Gets the results for the supplied train and test datasets. Now performs a deep copy of the classifier before it is built and evaluated (just in case the classifier is not initialized properly in buildClassifier()).

Specified by:

getResult in interface weka.experiment.SplitEvaluator

Overrides:

getResult in class weka.experiment.ClassifierSplitEvaluator

Parameters:

train - the training Instances.

test - the testing Instances.

Returns:

the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).

Throws:

java.lang.Exception - if a problem occurs while getting the results

setClassifier

public void setClassifier(weka.classifiers.Classifier newClassifier)

Sets the classifier.

Overrides:

setClassifier in class weka.experiment.ClassifierSplitEvaluator

Parameters:

newClassifier - the new classifier to use.

classifierTipText

public java.lang.String classifierTipText()

Returns the tip text for this property

Overrides:

classifierTipText in class weka.experiment.ClassifierSplitEvaluator

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.experiment.ClassifierSplitEvaluator

Returns:

the revision